here is my code that draws landmarks on hand using mediapipe
import cv2
import time
import mediapipe as mp
mp_holistic = mp.solutions.holistic
holistic_model = mp_holistic.Holistic(
min_detection_confidence=0.5,
min_tracking_confidence=0.5
)
# Initializing the drawing utils for drawing the facial landmarks on image
mp_drawing = mp.solutions.drawing_utils
# (0) in VideoCapture is used to connect to your computer's default camera
capture = cv2.VideoCapture(0)
# Initializing current time and precious time for calculating the FPS
previousTime = 0
currentTime = 0
while capture.isOpened():
# capture frame by frame
ret, frame = capture.read()
# resizing the frame for better view
frame = cv2.resize(frame, (800, 600))
# Converting the from BGR to RGB
image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Making predictions using holistic model
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
results = holistic_model.process(image)
image.flags.writeable = True
# Converting back the RGB image to BGR
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# Drawing the Facial Landmarks
# mp_drawing.draw_landmarks(
# image,
# results.face_landmarks,
# mp_holistic.FACEMESH_CONTOURS,
# mp_drawing.DrawingSpec(
# color=(255, 0, 255),
# thickness=1,
# circle_radius=1
# ),
# mp_drawing.DrawingSpec(
# color=(0, 255, 255),
# thickness=1,
# circle_radius=1
# )
# )
# Drawing Right hand Land Marks
mp_drawing.draw_landmarks(
image,
results.right_hand_landmarks,
mp_holistic.HAND_CONNECTIONS
)
for landmark in mp_holistic.HandLandmark:
print(landmark,landmark.value)
# Drawing Left hand Land Marks
mp_drawing.draw_landmarks(
image,
results.left_hand_landmarks,
mp_holistic.HAND_CONNECTIONS
)
# Calculating the FPS
currentTime = time.time()
fps = 1 / (currentTime - previousTime)
previousTime = currentTime
# Displaying FPS on the image
cv2.putText(image, str(int(fps)) + " FPS", (10, 70), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
# Display the resulting image
cv2.imshow("Facial and Hand Landmarks", image)
# Enter key 'q' to break the loop
if cv2.waitKey(5) & 0xFF == ord('q'):
break
# When all the process is done
# Release the capture and destroy all windows
capture.release()
cv2.destroyAllWindows()
for both left and right hand, but my goal is : to draw straight line between hand, in order to understand my question, let us discuess following image :
from the figure we can say for instance that line between hands should be perfectly horizontan (so angle should be zero, as if we consider following equation :
it is easy to say that in order to be perfectly horizontal lines , y coordinates should be equal to each other, so please help me to detect how to determine coordinates and how to draw line between two point? drawing is easy as cv2.line exist, but what about coordinates?
You're using the built-in Mediapipe function draw_landmarks
to handle all the drawings. This function takes an image, a normalized landmark list, and connections as inputs. However, the NormalizedLandmarkList
type in Mediapipe doesn’t support merging multiple landmark lists, making it difficult to pass landmarks for both hands to the function and find connections.
An alternative approach is to extract the coordinates from the hand landmarks and draw a line using the cv2.line
method, as you mentioned. Here’s the code to implement this approach:
right_hand_landmarks = results.right_hand_landmarks
left_hand_landmarks = results.left_hand_landmarks
# try to render a line if both hands are detected
if right_hand_landmarks and left_hand_landmarks:
# find the position of wrist landmark (as it is normalized, it should multiplied by width and height for x and y respectively)
right_wrist = np.array([right_hand_landmarks.landmark[0].x * image.shape[1], right_hand_landmarks.landmark[0].y * image.shape[0]]).astype("int")
left_wrist = np.array([left_hand_landmarks.landmark[0].x * image.shape[1], left_hand_landmarks.landmark[0].y * image.shape[0]]).astype("int")
# draw a line between two wrists
cv2.line(image, right_wrist, left_wrist, color=(255,255,255), thickness=3)
If you want to select another landmark other than the wrist
, check this link to see landmark indices.